{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cf4c3cba",
   "metadata": {},
   "source": [
    "# Getting Started with Chronos-2\n",
    "\n",
    "[![Open In SageMaker Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/amazon-science/chronos-forecasting/blob/main/notebooks/chronos-2-quickstart.ipynb)\n",
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](\n",
    "https://colab.research.google.com/github/amazon-science/chronos-forecasting/blob/main/notebooks/chronos-2-quickstart.ipynb)\n",
    "\n",
    "\n",
    "\n",
    "**Chronos-2** is a foundation model for time series forecasting that builds on [Chronos](https://arxiv.org/abs/2403.07815) and [Chronos-Bolt](https://aws.amazon.com/blogs/machine-learning/fast-and-accurate-zero-shot-forecasting-with-chronos-bolt-and-autogluon/). It offers significant improvements in capabilities and can handle diverse forecasting scenarios not supported by earlier models.\n",
    "\n",
    "| Capability | Chronos | Chronos-Bolt | Chronos-2 |\n",
    "|------------|---------|--------------|-----------|\n",
    "| Univariate Forecasting | ✅ | ✅ | ✅ |\n",
    "| Cross-learning across items | ❌ | ❌ | ✅ |\n",
    "| Multivariate Forecasting | ❌ | ❌ | ✅ |\n",
    "| Past-only (real/categorical) covariates | ❌ | ❌ | ✅ |\n",
    "| Known future (real/categorical) covariates | 🧩 | 🧩 | ✅ |\n",
    "| Fine-tuning support | ✅ | ✅ | ✅ |\n",
    "| Max. Context Length | 512 | 2048 | 8192 |\n",
    "\n",
    "🧩 Chronos/Chronos-Bolt do not natively support future covariates, but they can be combined with external covariate regressors (see [AutoGluon tutorial](https://auto.gluon.ai/stable/tutorials/timeseries/forecasting-chronos.html#incorporating-the-covariates)). This only models per-timestep effects, not effects across time. In contrast, Chronos-2 supports all covariate types natively.\n",
    "\n",
    "More details about Chronos-2 are available in the [technical report](https://www.arxiv.org/abs/2510.15821)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1d5f2e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install 'chronos-forecasting>=2.2[extras]' 'matplotlib'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fcc7e496",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "# Use only 1 GPU if available\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from chronos import BaseChronosPipeline, Chronos2Pipeline\n",
    "\n",
    "# Load the Chronos-2 pipeline\n",
    "# GPU recommended for faster inference, but CPU is also supported using device_map=\"cpu\"\n",
    "pipeline: Chronos2Pipeline = BaseChronosPipeline.from_pretrained(\"amazon/chronos-2\", device_map=\"cuda\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ef707b6",
   "metadata": {},
   "source": [
    "## Univariate Forecasting\n",
    "\n",
    "We start with a simple univariate forecasting example using the pandas API."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "39de5d7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input dataframe shape: (353500, 3)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-01 00:00:00</td>\n",
       "      <td>605.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-01 01:00:00</td>\n",
       "      <td>586.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-01 02:00:00</td>\n",
       "      <td>586.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-01 03:00:00</td>\n",
       "      <td>559.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-01 04:00:00</td>\n",
       "      <td>511.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  item_id            timestamp  target\n",
       "0      H1  1750-01-01 00:00:00   605.0\n",
       "1      H1  1750-01-01 01:00:00   586.0\n",
       "2      H1  1750-01-01 02:00:00   586.0\n",
       "3      H1  1750-01-01 03:00:00   559.0\n",
       "4      H1  1750-01-01 04:00:00   511.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load data as a long-format pandas data frame\n",
    "context_df = pd.read_csv(\"https://autogluon.s3.amazonaws.com/datasets/timeseries/m4_hourly/train.csv\")\n",
    "print(\"Input dataframe shape:\", context_df.shape)\n",
    "display(context_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7ebac5c4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output dataframe shape: (9936, 7)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>target_name</th>\n",
       "      <th>predictions</th>\n",
       "      <th>0.1</th>\n",
       "      <th>0.5</th>\n",
       "      <th>0.9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-30 04:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>624.867981</td>\n",
       "      <td>611.385132</td>\n",
       "      <td>624.867981</td>\n",
       "      <td>638.598816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-30 05:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>563.703125</td>\n",
       "      <td>546.655090</td>\n",
       "      <td>563.703125</td>\n",
       "      <td>578.665710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-30 06:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>521.589905</td>\n",
       "      <td>505.747498</td>\n",
       "      <td>521.589905</td>\n",
       "      <td>537.950867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-30 07:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>489.910767</td>\n",
       "      <td>473.671814</td>\n",
       "      <td>489.910767</td>\n",
       "      <td>508.854156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>H1</td>\n",
       "      <td>1750-01-30 08:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>471.144470</td>\n",
       "      <td>452.199402</td>\n",
       "      <td>471.144470</td>\n",
       "      <td>491.050293</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  item_id           timestamp target_name  predictions         0.1  \\\n",
       "0      H1 1750-01-30 04:00:00      target   624.867981  611.385132   \n",
       "1      H1 1750-01-30 05:00:00      target   563.703125  546.655090   \n",
       "2      H1 1750-01-30 06:00:00      target   521.589905  505.747498   \n",
       "3      H1 1750-01-30 07:00:00      target   489.910767  473.671814   \n",
       "4      H1 1750-01-30 08:00:00      target   471.144470  452.199402   \n",
       "\n",
       "          0.5         0.9  \n",
       "0  624.867981  638.598816  \n",
       "1  563.703125  578.665710  \n",
       "2  521.589905  537.950867  \n",
       "3  489.910767  508.854156  \n",
       "4  471.144470  491.050293  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pred_df = pipeline.predict_df(context_df, prediction_length=24, quantile_levels=[0.1, 0.5, 0.9])\n",
    "\n",
    "print(\"Output dataframe shape:\", pred_df.shape)\n",
    "display(pred_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e00816aa",
   "metadata": {},
   "source": [
    "**predict_df** supports the following arguments:\n",
    "- `df`: Long-format DataFrame with id, timestamp, and target column(s)\n",
    "- `future_df`: Optional DataFrame with future covariates (columns present in both df and future_df are treated as known future covariates)\n",
    "- `id_column`: Column with time series identifiers (default: \"item_id\")\n",
    "- `timestamp_column`: Column with timestamps (default: \"timestamp\")\n",
    "- `target`: Target column name(s) to forecast (default: \"target\")\n",
    "- `prediction_length`: Number of steps to forecast\n",
    "- `quantile_levels`: Quantiles to compute (default: [0.1, 0.2, ..., 0.9])\n",
    "\n",
    "Returns a DataFrame with forecasts including point predictions and quantiles."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a1bf0eb",
   "metadata": {},
   "source": [
    "## Forecasting with Covariates\n",
    "\n",
    "Chronos-2 can leverage covariates to improve forecast accuracy. We demonstrate this with two real-world examples."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "feeb38b5",
   "metadata": {},
   "source": [
    "### Energy Price Forecasting\n",
    "\n",
    "Forecast hourly energy prices for the next day using historical prices and day-ahead forecasts of load (Ampirion Load Forecast) and renewable energy generation (PV+Wind Forecast)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "87dad9a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>target</th>\n",
       "      <th>Ampirion Load Forecast</th>\n",
       "      <th>PV+Wind Forecast</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DE</td>\n",
       "      <td>2012-01-09 00:00:00</td>\n",
       "      <td>34.970001</td>\n",
       "      <td>16382.00</td>\n",
       "      <td>3569.527588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DE</td>\n",
       "      <td>2012-01-09 01:00:00</td>\n",
       "      <td>33.430000</td>\n",
       "      <td>15410.50</td>\n",
       "      <td>3315.274902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DE</td>\n",
       "      <td>2012-01-09 02:00:00</td>\n",
       "      <td>32.740002</td>\n",
       "      <td>15595.00</td>\n",
       "      <td>3107.307617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DE</td>\n",
       "      <td>2012-01-09 03:00:00</td>\n",
       "      <td>32.459999</td>\n",
       "      <td>16521.00</td>\n",
       "      <td>2944.620117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DE</td>\n",
       "      <td>2012-01-09 04:00:00</td>\n",
       "      <td>32.500000</td>\n",
       "      <td>17700.75</td>\n",
       "      <td>2897.149902</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id           timestamp     target  Ampirion Load Forecast  PV+Wind Forecast\n",
       "0  DE 2012-01-09 00:00:00  34.970001                16382.00       3569.527588\n",
       "1  DE 2012-01-09 01:00:00  33.430000                15410.50       3315.274902\n",
       "2  DE 2012-01-09 02:00:00  32.740002                15595.00       3107.307617\n",
       "3  DE 2012-01-09 03:00:00  32.459999                16521.00       2944.620117\n",
       "4  DE 2012-01-09 04:00:00  32.500000                17700.75       2897.149902"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>Ampirion Load Forecast</th>\n",
       "      <th>PV+Wind Forecast</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 00:00:00</td>\n",
       "      <td>20483.00</td>\n",
       "      <td>22284.005859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 01:00:00</td>\n",
       "      <td>19849.75</td>\n",
       "      <td>22878.673828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 02:00:00</td>\n",
       "      <td>19638.25</td>\n",
       "      <td>23632.283203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 03:00:00</td>\n",
       "      <td>19895.25</td>\n",
       "      <td>24635.945312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 04:00:00</td>\n",
       "      <td>20338.00</td>\n",
       "      <td>25584.935547</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id           timestamp  Ampirion Load Forecast  PV+Wind Forecast\n",
       "0  DE 2017-12-12 00:00:00                20483.00      22284.005859\n",
       "1  DE 2017-12-12 01:00:00                19849.75      22878.673828\n",
       "2  DE 2017-12-12 02:00:00                19638.25      23632.283203\n",
       "3  DE 2017-12-12 03:00:00                19895.25      24635.945312\n",
       "4  DE 2017-12-12 04:00:00                20338.00      25584.935547"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Energy price forecasting configuration\n",
    "target = \"target\"  # Column name containing the values to forecast (energy prices)\n",
    "prediction_length = 24  # Number of hours to forecast ahead\n",
    "id_column = \"id\"  # Column identifying different time series (countries/regions)\n",
    "timestamp_column = \"timestamp\"  # Column containing datetime information\n",
    "timeseries_id = \"DE\"  # Specific time series to visualize (Germany)\n",
    "\n",
    "# Load historical energy prices and past values of covariates\n",
    "energy_context_df = pd.read_parquet(\n",
    "    \"https://autogluon.s3.amazonaws.com/datasets/timeseries/electricity_price/train.parquet\"\n",
    ")\n",
    "energy_context_df[timestamp_column] = pd.to_datetime(energy_context_df[timestamp_column])\n",
    "display(energy_context_df.head())\n",
    "\n",
    "# Load future values of covariates\n",
    "energy_test_df = pd.read_parquet(\n",
    "    \"https://autogluon.s3.amazonaws.com/datasets/timeseries/electricity_price/test.parquet\"\n",
    ")\n",
    "energy_test_df[timestamp_column] = pd.to_datetime(energy_test_df[timestamp_column])\n",
    "energy_future_df = energy_test_df.drop(columns=target)\n",
    "display(energy_future_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0efd3ba3",
   "metadata": {
    "lines_to_next_cell": 1
   },
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>target_name</th>\n",
       "      <th>predictions</th>\n",
       "      <th>0.1</th>\n",
       "      <th>0.5</th>\n",
       "      <th>0.9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 00:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>22.242920</td>\n",
       "      <td>18.673723</td>\n",
       "      <td>22.242920</td>\n",
       "      <td>25.403454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 01:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>19.525620</td>\n",
       "      <td>14.904278</td>\n",
       "      <td>19.525620</td>\n",
       "      <td>23.316601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 02:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>17.415363</td>\n",
       "      <td>12.209047</td>\n",
       "      <td>17.415363</td>\n",
       "      <td>21.776979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 03:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>16.979263</td>\n",
       "      <td>11.165121</td>\n",
       "      <td>16.979263</td>\n",
       "      <td>21.435223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DE</td>\n",
       "      <td>2017-12-12 04:00:00</td>\n",
       "      <td>target</td>\n",
       "      <td>18.058651</td>\n",
       "      <td>12.096766</td>\n",
       "      <td>18.058651</td>\n",
       "      <td>23.166645</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id           timestamp target_name  predictions        0.1        0.5  \\\n",
       "0  DE 2017-12-12 00:00:00      target    22.242920  18.673723  22.242920   \n",
       "1  DE 2017-12-12 01:00:00      target    19.525620  14.904278  19.525620   \n",
       "2  DE 2017-12-12 02:00:00      target    17.415363  12.209047  17.415363   \n",
       "3  DE 2017-12-12 03:00:00      target    16.979263  11.165121  16.979263   \n",
       "4  DE 2017-12-12 04:00:00      target    18.058651  12.096766  18.058651   \n",
       "\n",
       "         0.9  \n",
       "0  25.403454  \n",
       "1  23.316601  \n",
       "2  21.776979  \n",
       "3  21.435223  \n",
       "4  23.166645  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate predictions with covariates\n",
    "energy_pred_df = pipeline.predict_df(\n",
    "    energy_context_df,\n",
    "    future_df=energy_future_df,\n",
    "    prediction_length=prediction_length,\n",
    "    quantile_levels=[0.1, 0.5, 0.9],\n",
    "    id_column=id_column,\n",
    "    timestamp_column=timestamp_column,\n",
    "    target=target,\n",
    ")\n",
    "display(energy_pred_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cef8aa47",
   "metadata": {
    "lines_to_next_cell": 1
   },
   "outputs": [],
   "source": [
    "# Visualization helper function\n",
    "def plot_forecast(\n",
    "    context_df: pd.DataFrame,\n",
    "    pred_df: pd.DataFrame,\n",
    "    test_df: pd.DataFrame,\n",
    "    target_column: str,\n",
    "    timeseries_id: str,\n",
    "    id_column: str = \"id\",\n",
    "    timestamp_column: str = \"timestamp\",\n",
    "    history_length: int = 256,\n",
    "    title_suffix: str = \"\",\n",
    "):\n",
    "    ts_context = context_df.query(f\"{id_column} == @timeseries_id\").set_index(timestamp_column)[target_column]\n",
    "    ts_pred = pred_df.query(f\"{id_column} == @timeseries_id and target_name == @target_column\").set_index(\n",
    "        timestamp_column\n",
    "    )[[\"0.1\", \"predictions\", \"0.9\"]]\n",
    "    ts_ground_truth = test_df.query(f\"{id_column} == @timeseries_id\").set_index(timestamp_column)[target_column]\n",
    "\n",
    "    last_date = ts_context.index.max()\n",
    "    start_idx = max(0, len(ts_context) - history_length)\n",
    "    plot_cutoff = ts_context.index[start_idx]\n",
    "    ts_context = ts_context[ts_context.index >= plot_cutoff]\n",
    "    ts_pred = ts_pred[ts_pred.index >= plot_cutoff]\n",
    "    ts_ground_truth = ts_ground_truth[ts_ground_truth.index >= plot_cutoff]\n",
    "\n",
    "    fig = plt.figure(figsize=(12, 3))\n",
    "    ax = fig.gca()\n",
    "    ts_context.plot(ax=ax, label=f\"historical {target_column}\", color=\"xkcd:azure\")\n",
    "    ts_ground_truth.plot(ax=ax, label=f\"future {target_column} (ground truth)\", color=\"xkcd:grass green\")\n",
    "    ts_pred[\"predictions\"].plot(ax=ax, label=\"forecast\", color=\"xkcd:violet\")\n",
    "    ax.fill_between(\n",
    "        ts_pred.index,\n",
    "        ts_pred[\"0.1\"],\n",
    "        ts_pred[\"0.9\"],\n",
    "        alpha=0.7,\n",
    "        label=\"prediction interval\",\n",
    "        color=\"xkcd:light lavender\",\n",
    "    )\n",
    "    ax.axvline(x=last_date, color=\"black\", linestyle=\"--\", alpha=0.5)\n",
    "    ax.legend(loc=\"upper left\")\n",
    "    ax.set_title(f\"{target_column} forecast for {timeseries_id} {title_suffix}\")\n",
    "    fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0b1c215e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize forecast with covariates\n",
    "plot_forecast(\n",
    "    energy_context_df,\n",
    "    energy_pred_df,\n",
    "    energy_test_df,\n",
    "    target_column=target,\n",
    "    timeseries_id=timeseries_id,\n",
    "    title_suffix=\"(with covariates)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3e684805",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare: forecast without covariates\n",
    "energy_pred_no_cov_df = pipeline.predict_df(\n",
    "    energy_context_df[[id_column, timestamp_column, target]],\n",
    "    future_df=None,\n",
    "    prediction_length=prediction_length,\n",
    "    quantile_levels=[0.1, 0.5, 0.9],\n",
    "    id_column=id_column,\n",
    "    timestamp_column=timestamp_column,\n",
    "    target=target,\n",
    ")\n",
    "\n",
    "plot_forecast(\n",
    "    energy_context_df,\n",
    "    energy_pred_no_cov_df,\n",
    "    energy_test_df,\n",
    "    target_column=target,\n",
    "    timeseries_id=timeseries_id,\n",
    "    title_suffix=\"(without covariates)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d60478f9",
   "metadata": {},
   "source": [
    "The comparison shows that Chronos-2 makes reasonable but imprecise predictions in univariate mode. However, with covariates, Chronos-2 effectively uses the load and renewable generation forecasts, producing significantly more accurate predictions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbb49405",
   "metadata": {},
   "source": [
    "### Retail Demand Forecasting\n",
    "\n",
    "Forecast next quarter's weekly store sales using historical sales, historical customer footfall (Customers), and known covariates indicating store operation (Open), promotion periods (Promo), and holidays (SchoolHoliday, StateHoliday)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "48a4b732",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Open</th>\n",
       "      <th>Promo</th>\n",
       "      <th>SchoolHoliday</th>\n",
       "      <th>StateHoliday</th>\n",
       "      <th>Customers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-01-13</td>\n",
       "      <td>32952.0</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3918.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-01-20</td>\n",
       "      <td>25978.0</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3417.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-01-27</td>\n",
       "      <td>33071.0</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3862.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-02-03</td>\n",
       "      <td>28693.0</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3561.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2013-02-10</td>\n",
       "      <td>35771.0</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4094.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  id  timestamp    Sales      Open     Promo  SchoolHoliday  StateHoliday  \\\n",
       "0  1 2013-01-13  32952.0  0.857143  0.714286            5.0           0.0   \n",
       "1  1 2013-01-20  25978.0  0.857143  0.000000            0.0           0.0   \n",
       "2  1 2013-01-27  33071.0  0.857143  0.714286            0.0           0.0   \n",
       "3  1 2013-02-03  28693.0  0.857143  0.000000            0.0           0.0   \n",
       "4  1 2013-02-10  35771.0  0.857143  0.714286            0.0           0.0   \n",
       "\n",
       "   Customers  \n",
       "0     3918.0  \n",
       "1     3417.0  \n",
       "2     3862.0  \n",
       "3     3561.0  \n",
       "4     4094.0  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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       "      <th>SchoolHoliday</th>\n",
       "      <th>StateHoliday</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-03</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-10</td>\n",
       "      <td>0.857143</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-17</td>\n",
       "      <td>0.714286</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-24</td>\n",
       "      <td>0.857143</td>\n",
       "      <td>0.714286</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <th>4</th>\n",
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       "      <td>0.714286</td>\n",
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      "text/plain": [
       "  id  timestamp      Open     Promo  SchoolHoliday  StateHoliday\n",
       "0  1 2015-05-03  0.714286  0.714286            0.0           1.0\n",
       "1  1 2015-05-10  0.857143  0.714286            0.0           0.0\n",
       "2  1 2015-05-17  0.714286  0.000000            0.0           1.0\n",
       "3  1 2015-05-24  0.857143  0.714286            0.0           0.0\n",
       "4  1 2015-05-31  0.714286  0.000000            0.0           1.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Retail forecasting configuration\n",
    "target = \"Sales\"  # Column name containing sales values to forecast\n",
    "prediction_length = 13  # Number of days to forecast ahead\n",
    "id_column = \"id\"  # Column identifying different products/stores\n",
    "timestamp_column = \"timestamp\"  # Column containing datetime information\n",
    "timeseries_id = \"1\"  # Specific time series to visualize (product/store ID)\n",
    "\n",
    "# Load historical sales and past values of covariates\n",
    "sales_context_df = pd.read_parquet(\"https://autogluon.s3.amazonaws.com/datasets/timeseries/retail_sales/train.parquet\")\n",
    "sales_context_df[timestamp_column] = pd.to_datetime(sales_context_df[timestamp_column])\n",
    "display(sales_context_df.head())\n",
    "\n",
    "# Load future values of covariates\n",
    "sales_test_df = pd.read_parquet(\"https://autogluon.s3.amazonaws.com/datasets/timeseries/retail_sales/test.parquet\")\n",
    "sales_test_df[timestamp_column] = pd.to_datetime(sales_test_df[timestamp_column])\n",
    "sales_future_df = sales_test_df.drop(columns=target)\n",
    "display(sales_future_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a56cf59c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>target_name</th>\n",
       "      <th>predictions</th>\n",
       "      <th>0.1</th>\n",
       "      <th>0.5</th>\n",
       "      <th>0.9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-03</td>\n",
       "      <td>Sales</td>\n",
       "      <td>28939.392578</td>\n",
       "      <td>25214.277344</td>\n",
       "      <td>28939.392578</td>\n",
       "      <td>32411.097656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-10</td>\n",
       "      <td>Sales</td>\n",
       "      <td>25541.919922</td>\n",
       "      <td>21921.324219</td>\n",
       "      <td>25541.919922</td>\n",
       "      <td>29191.929688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-17</td>\n",
       "      <td>Sales</td>\n",
       "      <td>23640.238281</td>\n",
       "      <td>20500.339844</td>\n",
       "      <td>23640.238281</td>\n",
       "      <td>26884.666016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-24</td>\n",
       "      <td>Sales</td>\n",
       "      <td>26778.261719</td>\n",
       "      <td>23318.355469</td>\n",
       "      <td>26778.261719</td>\n",
       "      <td>30162.820312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>2015-05-31</td>\n",
       "      <td>Sales</td>\n",
       "      <td>22679.361328</td>\n",
       "      <td>19722.287109</td>\n",
       "      <td>22679.361328</td>\n",
       "      <td>25990.042969</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  id  timestamp target_name   predictions           0.1           0.5  \\\n",
       "0  1 2015-05-03       Sales  28939.392578  25214.277344  28939.392578   \n",
       "1  1 2015-05-10       Sales  25541.919922  21921.324219  25541.919922   \n",
       "2  1 2015-05-17       Sales  23640.238281  20500.339844  23640.238281   \n",
       "3  1 2015-05-24       Sales  26778.261719  23318.355469  26778.261719   \n",
       "4  1 2015-05-31       Sales  22679.361328  19722.287109  22679.361328   \n",
       "\n",
       "            0.9  \n",
       "0  32411.097656  \n",
       "1  29191.929688  \n",
       "2  26884.666016  \n",
       "3  30162.820312  \n",
       "4  25990.042969  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate predictions with covariates\n",
    "sales_pred_df = pipeline.predict_df(\n",
    "    sales_context_df,\n",
    "    future_df=sales_future_df,\n",
    "    prediction_length=prediction_length,\n",
    "    quantile_levels=[0.1, 0.5, 0.9],\n",
    "    id_column=id_column,\n",
    "    timestamp_column=timestamp_column,\n",
    "    target=target,\n",
    ")\n",
    "display(sales_pred_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "447aab3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualize forecast with covariates\n",
    "plot_forecast(\n",
    "    sales_context_df,\n",
    "    sales_pred_df,\n",
    "    sales_test_df,\n",
    "    target_column=target,\n",
    "    timeseries_id=timeseries_id,\n",
    "    title_suffix=\"(with covariates)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d5974142",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Compare: forecast without covariates\n",
    "sales_pred_no_cov_df = pipeline.predict_df(\n",
    "    sales_context_df[[id_column, timestamp_column, target]],\n",
    "    future_df=None,\n",
    "    prediction_length=prediction_length,\n",
    "    quantile_levels=[0.1, 0.5, 0.9],\n",
    "    id_column=id_column,\n",
    "    timestamp_column=timestamp_column,\n",
    "    target=target,\n",
    ")\n",
    "\n",
    "plot_forecast(\n",
    "    sales_context_df,\n",
    "    sales_pred_no_cov_df,\n",
    "    sales_test_df,\n",
    "    target_column=target,\n",
    "    timeseries_id=timeseries_id,\n",
    "    title_suffix=\"(without covariates)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cf9f929",
   "metadata": {},
   "source": [
    "Chronos-2's univariate forecast is nearly flat with high uncertainty. In contrast, the forecast with covariates leverages promotion and holiday information to capture the true sales dynamics over the forecast horizon."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0e64196",
   "metadata": {},
   "source": [
    "## Cross-Learning with Joint Prediction\n",
    "\n",
    "Chronos-2 supports **cross-learning** through the `cross_learning=True` parameter, which enables the model to share information across all time series in a batch during prediction. This can be particularly beneficial when forecasting multiple related time series with short historical context."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "60585f64",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Example: Enable cross-learning for joint prediction\n",
    "# This assigns the same group ID to all time series, allowing information sharing\n",
    "joint_pred_df = pipeline.predict_df(\n",
    "    context_df,\n",
    "    prediction_length=24,\n",
    "    quantile_levels=[0.1, 0.5, 0.9],\n",
    "    cross_learning=True,  # Enable cross-learning\n",
    "    batch_size=100,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b427ca20",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info alert-light\" role=\"alert\">\n",
    "\n",
    "### Important Considerations for Cross-Learning\n",
    "\n",
    "When using `cross_learning=True`, keep these caveats in mind:\n",
    "\n",
    "- **Task-dependent results**: Cross-learning may not always improve forecasts and could worsen performance for some tasks. Evaluate this feature for your specific use case.\n",
    "\n",
    "- **Batch size dependency**: Results become dependent on batch size. Very large batch sizes may not provide benefits as they deviate from the maximum group size used during pretraining. For optimal results, consider using a batch size around 100 (as used in the paper).\n",
    "\n",
    "- **Input homogeneity**: This feature works best with homogeneous inputs (e.g., multiple univariate time series of the same type). Mixing different task types may lead to unexpected behavior.\n",
    "\n",
    "- **Short context benefit**: Cross-learning is most helpful when individual time series have limited historical context, as the model can leverage patterns from related series in the batch.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c16f90c",
   "metadata": {},
   "source": [
    "## (Advanced) Numpy/torch API\n",
    "\n",
    "For advanced use cases, Chronos-2 provides a lower-level numpy/torch API via the `predict_quantiles` method.\n",
    "\n",
    "The `predict_quantiles` method accepts:\n",
    "- `inputs`: Time series to forecast (see formats below)\n",
    "- `prediction_length`: Number of timesteps to forecast\n",
    "- `quantile_levels`: List of quantiles to compute\n",
    "\n",
    "Two input formats are supported:\n",
    "1. **3D array**: `(batch_size, num_variates, history_length)` for forecasting without covariates\n",
    "2. **List of dicts**: Each dict contains:\n",
    "   - `target`: 1D or 2D array of shape `(history_length,)` or `(num_variates, history_length)`\n",
    "   - `past_covariates` (optional): Dict mapping covariate names to 1D arrays of length `history_length`\n",
    "   - `future_covariates` (optional): Dict mapping covariate names to 1D arrays of length `prediction_length`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "49e9d93a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Univariate output shapes: torch.Size([1, 24, 3]) torch.Size([1, 24])\n"
     ]
    }
   ],
   "source": [
    "# Univariate forecasting\n",
    "inputs = np.random.randn(32, 1, 100)\n",
    "quantiles, mean = pipeline.predict_quantiles(\n",
    "    inputs, prediction_length=24, quantile_levels=[0.1, 0.5, 0.9]\n",
    ")\n",
    "print(\"Univariate output shapes:\", quantiles[0].shape, mean[0].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "41d95e35",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Multivariate output shapes: torch.Size([3, 48, 3]) torch.Size([3, 48])\n"
     ]
    }
   ],
   "source": [
    "# Multivariate forecasting\n",
    "inputs = np.random.randn(32, 3, 512)\n",
    "quantiles, mean = pipeline.predict_quantiles(\n",
    "    inputs, prediction_length=48, quantile_levels=[0.1, 0.5, 0.9]\n",
    ")\n",
    "print(\"Multivariate output shapes:\", quantiles[0].shape, mean[0].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "879cf65b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Univariate with covariates output shapes: torch.Size([1, 64, 3]) torch.Size([1, 64])\n"
     ]
    }
   ],
   "source": [
    "# Univariate forecasting with covariates\n",
    "prediction_length = 64\n",
    "inputs = [\n",
    "    {\n",
    "        \"target\": np.random.randn(200),\n",
    "        \"past_covariates\": {\"temperature\": np.random.randn(200), \"precipitation\": np.random.randn(200)},\n",
    "        \"future_covariates\": {\"temperature\": np.random.randn(prediction_length)},\n",
    "    }\n",
    "    for _ in range(16)\n",
    "]\n",
    "quantiles, mean = pipeline.predict_quantiles(\n",
    "    inputs, prediction_length=prediction_length, quantile_levels=[0.1, 0.5, 0.9]\n",
    ")\n",
    "print(\"Univariate with covariates output shapes:\", quantiles[0].shape, mean[0].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "08c7556e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Multivariate with categorical covariates output shapes: torch.Size([2, 96, 3]) torch.Size([2, 96])\n"
     ]
    }
   ],
   "source": [
    "# Multivariate forecasting with categorical covariates\n",
    "prediction_length = 96\n",
    "inputs = [\n",
    "    {\n",
    "        \"target\": np.random.randn(2, 1000),\n",
    "        \"past_covariates\": {\n",
    "            \"temperature\": np.random.randn(1000),\n",
    "            \"weather_type\": np.random.choice([\"sunny\", \"cloudy\", \"rainy\"], size=1000),\n",
    "        },\n",
    "        \"future_covariates\": {\n",
    "            \"temperature\": np.random.randn(prediction_length),\n",
    "            \"weather_type\": np.random.choice([\"sunny\", \"cloudy\", \"rainy\"], size=prediction_length),\n",
    "        },\n",
    "    }\n",
    "    for _ in range(10)\n",
    "]\n",
    "quantiles, mean = pipeline.predict_quantiles(\n",
    "    inputs, prediction_length=prediction_length, quantile_levels=[0.1, 0.5, 0.9]\n",
    ")\n",
    "print(\"Multivariate with categorical covariates output shapes:\", quantiles[0].shape, mean[0].shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c99a5ae1",
   "metadata": {},
   "source": [
    "## Fine-Tuning\n",
    "\n",
    "Chronos-2 supports fine-tuning on your own data. You may either fine-tune all weights of the model (_full fine-tuning_) or a [low rank adapter (LoRA)](https://huggingface.co/docs/peft/en/package_reference/lora), which significantly reduces the number of trainable parameters.\n",
    "\n",
    "<div class=\"alert alert-warning alert-light\" role=\"alert\">\n",
    "\n",
    "**Note:** Fine-tuning functionality is intended for advanced users. The default fine-tuning hyperparameters may not always improve accuracy for your specific use case. We recommend experimenting with different hyperparameters. In case of limited data (too few and/or too short series), fine-tuning may not improve over zero-shot (and may even worsen accuracy sometimes).\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae26a137",
   "metadata": {},
   "source": [
    "### Fine-Tuning API\n",
    "\n",
    "The `fit` method accepts:\n",
    "- `inputs`: Time series for fine-tuning (same format as predict_quantiles)\n",
    "- `finetune_mode`: `\"full\"` or `\"lora\"`\n",
    "- `lora_config`: The [`LoraConfig`](https://huggingface.co/docs/peft/en/package_reference/lora#peft.LoraConfig), in case `finetune_mode=\"lora\"`\n",
    "- `prediction_length`: Forecast horizon for fine-tuning\n",
    "- `validation_inputs`: Optional validation data (same format as inputs)\n",
    "- `learning_rate`: Optimizer learning rate (default: 1e-6, we recommend a higher learning rate such as 1e-5 for LoRA)\n",
    "- `num_steps`: Number of training steps (default: 1000)\n",
    "- `batch_size`: Batch size for training (default: 256)\n",
    "\n",
    "Returns a new pipeline with the fine-tuned model.\n",
    "\n",
    "Please read the docstring for details about specific arguments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "75915194",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare data for fine-tuning using the retail sales dataset\n",
    "known_covariates = [\"Open\", \"Promo\", \"SchoolHoliday\", \"StateHoliday\"]\n",
    "past_covariates = [\"Customers\"]\n",
    "\n",
    "train_inputs = []\n",
    "for item_id, group in sales_context_df.groupby(\"id\"):\n",
    "    train_inputs.append({\n",
    "        \"target\": group[target].values,\n",
    "        \"past_covariates\": {col: group[col].values for col in past_covariates + known_covariates},\n",
    "        # Future values of covariates are not used during training.\n",
    "        # However, we need to include their names to indicate that these columns will be available at prediction time\n",
    "        \"future_covariates\": {col: None for col in known_covariates},\n",
    "    })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ea999650",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Could not estimate the number of tokens of the input, floating-point operations will not be computed\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      \n",
       "      <progress value='1000' max='1000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      [1000/1000 01:13, Epoch 1/9223372036854775807]\n",
       "    </div>\n",
       "    <table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       " <tr style=\"text-align: left;\">\n",
       "      <th>Step</th>\n",
       "      <th>Training Loss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>100</td>\n",
       "      <td>0.645200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>200</td>\n",
       "      <td>0.531200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>300</td>\n",
       "      <td>0.506000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>400</td>\n",
       "      <td>0.463900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>500</td>\n",
       "      <td>0.458000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>600</td>\n",
       "      <td>0.523900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>700</td>\n",
       "      <td>0.460600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>800</td>\n",
       "      <td>0.431000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>900</td>\n",
       "      <td>0.443300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1000</td>\n",
       "      <td>0.501900</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table><p>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fine-tune the model by default full fine-tuning will be performed\n",
    "finetuned_pipeline = pipeline.fit(\n",
    "    inputs=train_inputs,\n",
    "    prediction_length=13,\n",
    "    num_steps=1000, \n",
    "    learning_rate=1e-5,\n",
    "    batch_size=32,\n",
    "    logging_steps=100,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d77f7a9f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use the fine-tuned model for predictions\n",
    "finetuned_pred_df = finetuned_pipeline.predict_df(\n",
    "    sales_context_df,\n",
    "    future_df=sales_future_df,\n",
    "    prediction_length=13,\n",
    "    quantile_levels=[0.1, 0.5, 0.9],\n",
    "    id_column=\"id\",\n",
    "    timestamp_column=\"timestamp\",\n",
    "    target=\"Sales\",\n",
    ")\n",
    "\n",
    "plot_forecast(\n",
    "    sales_context_df,\n",
    "    finetuned_pred_df,\n",
    "    sales_test_df,\n",
    "    target_column=\"Sales\",\n",
    "    timeseries_id=\"1\",\n",
    "    title_suffix=\"(full fine-tuned)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7944046c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Could not estimate the number of tokens of the input, floating-point operations will not be computed\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "      \n",
       "      <progress value='1000' max='1000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      [1000/1000 01:53, Epoch 1/9223372036854775807]\n",
       "    </div>\n",
       "    <table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       " <tr style=\"text-align: left;\">\n",
       "      <th>Step</th>\n",
       "      <th>Training Loss</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>100</td>\n",
       "      <td>0.752000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>200</td>\n",
       "      <td>0.617800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>300</td>\n",
       "      <td>0.596500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>400</td>\n",
       "      <td>0.539700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>500</td>\n",
       "      <td>0.544400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>600</td>\n",
       "      <td>0.605700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>700</td>\n",
       "      <td>0.546800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>800</td>\n",
       "      <td>0.511900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>900</td>\n",
       "      <td>0.537200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1000</td>\n",
       "      <td>0.583500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table><p>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fine-tune the model with LoRA\n",
    "lora_finetuned_pipeline = pipeline.fit(\n",
    "    inputs=train_inputs,\n",
    "    prediction_length=13,\n",
    "    num_steps=1000,\n",
    "    learning_rate=1e-4,\n",
    "    batch_size=32,\n",
    "    logging_steps=100,\n",
    "    finetune_mode=\"lora\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "44e5d367",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Use the LoRA fine-tuned model for predictions\n",
    "lora_finetuned_pred_df = lora_finetuned_pipeline.predict_df(\n",
    "    sales_context_df,\n",
    "    future_df=sales_future_df,\n",
    "    prediction_length=13,\n",
    "    quantile_levels=[0.1, 0.5, 0.9],\n",
    "    id_column=\"id\",\n",
    "    timestamp_column=\"timestamp\",\n",
    "    target=\"Sales\",\n",
    ")\n",
    "\n",
    "plot_forecast(\n",
    "    sales_context_df,\n",
    "    lora_finetuned_pred_df,\n",
    "    sales_test_df,\n",
    "    target_column=\"Sales\",\n",
    "    timeseries_id=\"1\",\n",
    "    title_suffix=\"(LoRA fine-tuned)\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c899976",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "jupytext": {
   "cell_metadata_filter": "-all",
   "main_language": "python",
   "notebook_metadata_filter": "-all"
  },
  "kernelspec": {
   "display_name": "chronos-forecasting",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
